{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision import transforms\n",
    "import torch\n",
    "import torch.optim as optim\n",
    "from torch.utils.data import random_split, DataLoader\n",
    "import time\n",
    "import cv2\n",
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "#Local Imports\n",
    "from transforms import Normalize,SequenceRandomTransform,ToTensor\n",
    "from dataset import HeadposeDataset, DatasetFromSubset\n",
    "from model import FSANet\n",
    "from utils import draw_axis\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x (images) shape:  (122415, 64, 64, 3)\n",
      "y (poses) shape:  (122415, 3)\n"
     ]
    }
   ],
   "source": [
    "augmentation = SequenceRandomTransform()\n",
    "\n",
    "data_path = '../data/type1/train'\n",
    "\n",
    "hdb = HeadposeDataset(data_path,transform=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yaw: 21.16, Pitch: -6.89, Roll: -11.83\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fd6b058ff10>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Choose Input Image Index from Dataset\n",
    "idx = 26\n",
    "x,y = hdb[idx]\n",
    "print(f'Yaw: {y[0]:.2f}, Pitch: {y[1]:.2f}, Roll: {y[2]:.2f}')\n",
    "x_real = x.copy()\n",
    "x_aug = augmentation(x_real).copy()\n",
    "\n",
    "draw_axis(x_real,y[0],y[1],y[2],size=20)\n",
    "draw_axis(x_aug,y[0],y[1],y[2],size=20)\n",
    "\n",
    "fig=plt.figure(figsize=(10, 10), dpi= 80, facecolor='w', edgecolor='k')\n",
    "#Draw Original Input x\n",
    "plt.subplot(121)\n",
    "plt.title('Original')\n",
    "plt.imshow(x_real[:,:,::-1]) #show image as rgb\n",
    "#Draw Augmented Input x\n",
    "plt.subplot(122)\n",
    "plt.title('Augmented')\n",
    "plt.imshow(x_aug[:,:,::-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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